T-S Fuzzy Coordinated Control for Power Unit Based on Multi-objective Optimization

被引:0
|
作者
Hao Wan-jun [1 ]
Qiao Yan-hui [1 ]
Li Ze [1 ]
Wu Yong-zhi [1 ]
Gao Han-wen [1 ]
Yang Jun [2 ]
机构
[1] Suzhou Univ Sience & Tecnol, Coll Mech & Elect Engn, Suzhou 215011, Peoples R China
[2] Northeastern Univ, Coll Informat Sci & Engn, Senyang 110819, Peoples R China
基金
中国国家自然科学基金;
关键词
Boiler-turbine system; Coordinated control; Multi-objective Optimization; particle swarm optimization; Pole assignment; T-S Fuzzy Control; OPERATION;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Based on multi-objective optimization control, fuzzy state feedback control and Set Point tracking control strategy, A novel scheme for the coordinated control of power units is presented. Firstly, a fuzzy state space model of boiler-turbine system is built. Then, based on the model and pole placement design, a state feedback controller with asymptotic tracking performance is proposed. Because the system has nonlinear, strong coupling, variable condition, parameter time-varying characteristics, which led to the optimum parameters of pole placement are difficult to determine. In order to guarantee dynamic performance, stability and control variable constraints of the system, a multi-objective optimization method for pole placement based on particle swarm optimization is exploited. This control system has good tracking property with zero steady-state error and can reject input disturbances, the controller works well even if some parameters change. Simulation results show that the system designed by the proposed method gives satisfactory regulation quality within wide operating range.
引用
收藏
页码:3639 / 3644
页数:6
相关论文
共 50 条
  • [1] Multi-Objective Control for Continuous T-S Fuzzy Systems Based on Passive Performance
    Li Yan-Jiang
    Duan Guang-Ren
    2011 30TH CHINESE CONTROL CONFERENCE (CCC), 2011, : 2958 - 2963
  • [2] A robust multi-objective DPDC for uncertain T-S fuzzy systems
    Razavi-Panah, Jafar
    Majd, Vahid Johari
    FUZZY SETS AND SYSTEMS, 2008, 159 (20) : 2749 - 2762
  • [3] A multi-objective optimization Method for coordinated control
    Gao Yunfeng
    Hu Hua
    Wang Tao
    Yang Xiaoguang
    ADVANCED TRANSPORTATION, PTS 1 AND 2, 2011, 97-98 : 942 - +
  • [4] Reverse-Order Multi-Objective Evolution Algorithm for Multi-Objective Observer-Based Fault-Tolerant Control of T-S Fuzzy Systems
    Chen, Bor-Sen
    Lee, Min-Yen
    Chen, Wei-Yu
    Zhang, Weihai
    IEEE ACCESS, 2021, 9 : 1556 - 1574
  • [5] Design for TCSC multi-objective controller using T-S fuzzy model
    Wang, Bao-Hua
    Zhang, Yong-Fei
    Gaodianya Jishu/High Voltage Engineering, 2010, 36 (02): : 537 - 541
  • [6] Multi-objective T-S fuzzy control of Covid-19 spread model: An LMI approach
    Najarzadeh, Reza
    Asemani, Mohammad Hassan
    Dehghani, Maryam
    Shasadeghi, Mokhtar
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2023, 79
  • [7] Multi-objective coordinated optimization of power system with wind power accommodation
    Liu, Yang
    Hao, Lichao
    Xing, Zuoxia
    Jiang, Zhanpeng
    Xu, Jian
    ENERGY REPORTS, 2022, 8 : 188 - 195
  • [8] Multi-objective reactive power and voltage control based on fuzzy optimization strategy and fuzzy adaptive particle swarm
    Zhang, Wen
    Liu, Yutian
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2008, 30 (09) : 525 - 532
  • [9] Coordinated control system modelling of ultra-supercritical unit based on a new T-S fuzzy structure
    Hou, Guolian
    Du, Huan
    Yang, Yu
    Huang, Congzhi
    Zhang, Jianhua
    ISA TRANSACTIONS, 2018, 74 : 120 - 133
  • [10] Coordinated control of EPS and ESP based on function allocation and multi-objective fuzzy decision
    Zhang, Rongyun
    Huang, He
    Chen, Wuwei
    Zhao, Linfeng
    Yang, Jun
    Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2014, 50 (06): : 99 - 106